The research advances, S&T capabilities showcased at DDDAS2020(*), are stemming from the DDDAS (Dynamic Data Driven Applications Systems) paradigm, whereby instrumentation data are dynamically integrated into an executing application model while in reverse the executing model controls the instrumentation. DDDAS plays a key role in creating capabilities advances in many application areas and is also driving advances in foundational methods, through system-level (as well as subsystems-level) representation, that includes comprehensive principle- and physics-based-models and instrumentation, uncertainty quantification, estimation, observation, sampling, planning and control.

Overtime the DDDAS paradigm has shown the ability to engender new capabilities in (but not limited to) aerospace, bio-, geo-, space-, and medical sciences, critical infrastructures, cyber security, and resilient systems - the scope of application areas ranges “from the nano-scale to the extra-terra-scale”.

This new kind of Systems thinking through DDDAS, entails multidisciplinary collaborative research and advances in fundamental areas such as stochastic systems, modeling, simulation, sensing, inference, planning, control, decision support, learning, optimization and cyber infrastructures, and permeates a great many areas – Estimation, Control and Machine Learning, Informative Planning and Decision support; the control of sparsity in Networks, and to quantify utility of data to deal with Big Data. In Computation, to structure resources optimally and, most recently, in Quantum Computation (QC), DDDAS provides mechanisms for Sample and Query operators, as well as utilizing the prospect of QC for more efficient closed-loop symbiosis. In T&E, DDDAS creates capabilities for lifetime assessment and optimization of the performance of components and systems incorporating them.

The DDDAS community has made significant progress in closing the loop between Data and Knowledge, through improved modeling processes, understanding and mitigating model error with the aid of instrumentation, and controlling the instrumentation to turn the Big Datta deluge into smart data regimes. Identified new opportunities in QC and T&E are expanding the impact of DDDAS.

Call for Contributions

The conference is a forum to present and discuss advances, and opportunities for advances, in a wide set of application areas and their underlying foundational methods. Participants from academia, industry, government and international counterparts will report original work where DDDAS research is advancing scientific frontiers, engendering new engineering capabilities, and adaptively optimizing operational processes. The conference spans a broad set of topics and interests as highlighted above.

Important Dates - Paper Submission Processes and Deadlines

April 30, 2020: 1-page Abstract [IEEE format] via EasyChair

May 15, 2020: Invitation to paper submission

June 15, 2020: Paper submission

July 15, 2020: Notification of decision (presentation type) with reviews

August 15, 2020: Camera ready paper

NOTICE: The DDDAS2020 Organizing Committee appreciates your patience and cooperation with the conference changes as the upheaval of covid19 has created and restrictions placed upon all in the research community. Presently, the goal is for an in-person conference in Boston and likely hosted by MIT. Additional considerations include a virtual conference, given the overall environment with the covid19 pandemic, and possible travel restrictions continuing into the Fall. As changes arise, updates will be sent on the possible arrangements as the conditions become clearer in the months ahead